{"id":"W4284958110","doi":"10.1039/d2bm00485b","title":"Interplay of matrix stiffness and stress relaxation in directing osteogenic differentiation of mesenchymal stem cells","year":2022,"lang":"en","type":"article","venue":"Biomaterials Science","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Hôpital Saint-François d'Assise; Centre hospitalier universitaire de Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Bordeaux; Agence Nationale de la Recherche; Centre québécois sur les matériaux fonctionnels","keywords":"Mesenchymal stem cell; Self-healing hydrogels; Chemistry; Stress relaxation; Stiffness; Cell biology; Matrix (chemical analysis); Relaxation (psychology); Biophysics; Stem cell; Acrylamide; Materials science; Polymer chemistry; Composite material; Biology; Polymer; Neuroscience; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000378141,0.00005645355,0.00009794011,0.0001111931,0.00007909797,0.00001778577,0.0001402533,0.00002331819,0.00002762201],"category_scores_gemma":[0.00002248047,0.00005589301,0.000021831,0.0001782821,0.00005957155,0.00001030605,0.0002486682,0.00001500898,2.21192e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002030321,"about_ca_system_score_gemma":0.0000443648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007686204,"about_ca_topic_score_gemma":0.00001848087,"domain_scores_codex":[0.9992539,0.00006316788,0.000242571,0.0001985081,0.0001435901,0.0000983051],"domain_scores_gemma":[0.9995717,0.000009466192,0.0002157995,0.0001314286,0.00005093028,0.00002060892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003937108,0.00003873591,0.0007892381,0.00002235511,0.000003237436,2.65557e-7,0.0001365223,0.00004806718,0.9983736,0.0000815194,0.000002330519,0.0004647983],"study_design_scores_gemma":[0.0001584644,0.00009614389,0.004893891,0.00001489797,0.000004535896,0.000004769796,0.0003814247,0.0006688477,0.9936762,0.00001239925,0.0000329139,0.00005543819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990461,0.0001054349,0.0001582138,0.000007278752,0.0004691815,0.0001078069,0.000085494,0.000002680357,0.00001781913],"genre_scores_gemma":[0.9998327,0.00001846079,0.0000648695,0.000002061037,0.00001399948,0.00001073321,0.00002125718,0.000004509418,0.00003143711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004697286,"threshold_uncertainty_score":0.2279251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008120688910448063,"score_gpt":0.2591257930032453,"score_spread":0.2510051040927972,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}